Key result
The MAPAC Cardio-PreTest model predicted significant coronary artery disease with a C-statistic of 0.654 (95% CI, 0.618-0.693) and improved risk classification over the ESC recommended approach.
Why the study?
Acute nontraumatic chest pain is a frequent reason for consultation and presents a diagnostic challenge, prompting the estimation of significant CAD risk when infarction is ruled out by non-diagnostic ECG and negative troponins.
Does the MAPAC Cardio-PreTest model improve the prediction of significant CAD compared to the ESC recommended approach in patients with acute chest pain without infarction in the emergency department?
Observational (n=1,625)
Yes
Does the MAPAC Cardio-PreTest model improve the prediction of significant CAD compared to the ESC recommended approach in patients with acute chest pain without infarction in the emergency department?
Effect estimate: C-statistic 0.654 (95% CI 0.618-0.693)
The MAPAC Cardio-PreTest model provides an online tool that improves the individualized probability estimation of significant CAD in ED patients with acute chest pain without infarction compared to current ESC recommendations.
May aid CAD risk stratification in ED chest pain; leaves open prospective validation before practice change.
Acute nontraumatic chest pain is a frequent reaso n for consultation in emergency departments and represents a diagnostic challenge. The objective is to estimate the risk of significant coronary artery disease (CAD) in patients with cardiogenic acute chest pain for whom the diagnosis of infarction was ruled out in the emergency department with a nondiagnostic ECG and negative high-sensitivity troponins. We prospectively recruited 1625 patients from emergency departments of seven Spanish hospitals. The outcome was presence of significant CAD determined by presence of ischaemia in functional tests or more than 70% stenosis in imaging tests. In this study, we developed a predictive model and evaluated its performance and clinical utility. The prevalence of significant CAD was 14% [227/1625; 95% confidence interval (CI), 12-16]. MAPAC Cardio-PreTest model included seven predictors: age, sex, smoking, history of hypertension, family history of CAD, history of hyperuricaemia, and type of chest pain. The optimism-adjusted model discrimination was C-statistic 0.654 (95% CI, 0.618-0.693). Calibration plot showed good agreement between the predicted and observed risks, and calibration slope was 0.880 (95% CI, 0.731-1.108) and calibration-in-the-large -0.001 (95% CI, -0.141 to 0.132). The model increased net benefit and improved risk classification over the recommended approach by the European Society of Cardiology [Net Reclassification Index (NRI) of events = 5.3%, NRI of nonevents = 7.0%]. MAPAC Cardio-PreTest model is an online prediction tool to estimate the individualised probability of significant CAD in patients with acute chest pain without a diagnosis of infarction in emergency department. The model was more useful than the current alternatives in helping patients and clinicians make individually tailored choices about the intensity of monitoring or additional coronary tests.
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Fernández‐Félix et al. (2022) conducted an observational in Acute chest pain without infarction (n=1,625). MAPAC Cardio-PreTest model vs. European Society of Cardiology recommended approach was evaluated on Presence of significant CAD determined by presence of ischaemia in functional tests or more than 70% stenosis in imaging tests (C-statistic 0.654, 95% CI 0.618-0.693). The MAPAC Cardio-PreTest model predicted significant coronary artery disease with a C-statistic of 0.654 (95% CI, 0.618-0.693) and improved risk classification over the ESC recommended approach.
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